Nucleoside Analogue Reverse Transcriptase Inhibitors Differentially Inhibit Human LINE-1 Retrotransposition
Bibliographic record
Abstract
BACKGROUND: Intact LINE-1 elements are the only retrotransposons encoded by the human genome known to be capable of autonomous replication. Numerous cases of genetic disease have been traced to gene disruptions caused by LINE-1 retrotransposition events in germ-line cells. In addition, genomic instability resulting from LINE-1 retrotransposition in somatic cells has been proposed as a contributing factor to oncogenesis and to cancer progression. LINE-1 element activity may also play a role in normal physiology. METHODS AND PRINCIPAL FINDINGS: Using an in vitro LINE-1 retrotransposition reporter assay, we evaluated the abilities of several antiretroviral compounds to inhibit LINE-1 retrotransposition. The nucleoside analogue reverse transcriptase inhibitors (nRTIs): stavudine, zidovudine, tenofovir disoproxil fumarate, and lamivudine all inhibited LINE-1 retrotransposition with varying degrees of potencies, while the non-nucleoside HIV-1 reverse transcriptase inhibitor nevirapine showed no effect. CONCLUSIONS/SIGNIFICANCE: Our data demonstrates the ability for nRTIs to suppress LINE-1 retrotransposition. This is immediately applicable to studies aimed at examining potential roles for LINE-1 retrotransposition in physiological processes. In addition, our data raises novel safety considerations for nRTIs based on their potential to disrupt physiological processes involving LINE-1 retrotransposition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".